Towards Sensor Database Systems
MDM '01 Proceedings of the Second International Conference on Mobile Data Management
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Impact of Data Compression on Energy Consumption of Wireless-Networked Handheld Devices
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A Survey on Data Compression in Wireless Sensor Networks
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
EasiPC: A Packet Compression Mechanism for Embedded WSN
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Query Processing in Sensor Networks
IEEE Pervasive Computing
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This paper presents a novel method for optimizing sliding window based continuous queries. We deal with two categories of aggregation operations: stepwise aggregation (e.g. COUNT) and direct aggregation (e.g. MEDIAN). Our approach is, by using packet merging or compression techniques, to reduce the data size to the best extent, so that the total performance is optimal. A QoS weight item is specified together with a query, in which the importance of the four factors, power, delay, accuracy and error rate can be expressed. An optimal query plan can be obtained by studying all the factors simultaneously, leading to the minimum cost. Experiments are conducted to validate the effectiveness of the proposed method.